Search results

Given the dearth of thorough summaries in the literature, this systematic review and bibliometric analysis attempt to take a meticulous approach meant to present knowledge on the constantly developing subject of stock market volatility during crises. In outline, this study aims to map the extant literature available on stock market volatility during crisis periods.

The present study reviews 1,283 journal articles from the Scopus database published between 1994 and 2022, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 flow diagram. Bibliometric analysis through software like R studio and VOSviewer has been performed, that is, annual publication trend analysis, journal analysis, citation analysis, author influence analysis, analysis of affiliations, analysis of countries and regions, keyword analysis, thematic mapping, co-occurrence analysis, bibliographic coupling, co-citation analysis, Bradford’s law and Lotka’s law, to map the existing literature and identify the gaps.

The literature on the effects of crises on volatility in financial markets has grown in recent years. It was discovered that volatility intensified during crises. This increased volatility can be linked to COVID-19 and the global financial crisis of 2008, as both had massive effects on the world economy. Moreover, we identify specific patterns and factors contributing to increased volatility, providing valuable insights for further research and decision-making.

The present study is confined to the areas of economics, econometrics and finance, business, management and accounting and social sciences. Future studies could be conducted considering a broader perspective.

Most of the available literature has focused on the impact of some particular crises on the volatility of financial markets. The present study is not limited to some specific crises, and the suggested research directions will serve as a guide for future research.

We present an approach for pricing American put options with a regime-switching volatility. Our method reveals that the option price can be expressed as the sum of two components: the price of a European put option and the premium associated with the early exercise privilege. Our analysis demonstrates that, under these conditions, the perpetual put option consistently commands a higher price during periods of high volatility compared to those of low volatility. Moreover, we establish that the optimal exercise boundary is lower in high-volatility regimes than in low-volatility regimes. Additionally, we develop an analytical framework to describe American puts with an Erlang-distributed random-time horizon, which allows us to propose a numerical technique for approximating the value of American puts with finite expiry. We also show that a combined approach involving randomization and Richardson extrapolation can be a robust numerical algorithm for estimating American put prices with finite expiry.

This paper aims to investigate the dynamic volatility connectedness among 13 G20 countries by using the volatility indices.

The connectedness approach based on the time-varying parameter vector autoregression model has been used to investigate the linkage. The period of study is from 1 January 2014 to 20 April 2023.

This analysis revealed that volatility connectedness among the countries during COVID-19 and Russia–Ukraine conflict had increased significantly. Furthermore, analysis has indicated that investors had not anticipated the World Health Organization announcement of COVID-19 as a global pandemic. Contrarily, investors had anticipated the Russian invasion of Ukraine, evident in a significant rise in volatility before and after the invasion. In addition, the transmission of volatility is from developed to developing countries. Developed countries are NET volatility transmitters, whereas developing countries are NET volatility receivers. Finally, the ordinary least square regression result suggests that the volatility connectedness index is informative of stock market dynamics.

The connectedness approach has been widely used to estimate the dynamic connectedness among market indices, cryptocurrencies, sectoral indices, enegy commodities and metals. To the best of the authors’ knowledge, none of the previous studies have directly used the volatility indices to measure the volatility connectedness. Hence, this study is the first of its kind that has used volatility indices to measure the volatility connectedness among the countries.

This paper investigates the information content of implied volatilities inferred from individual stock options quoted over-the-counter (OTC). First, we examine whether the implied volatility has better explanatory power than historical volatility for forecasting future realized volatility of the underlying stock return. Next, we analyze the properties of volatility spreads, the difference between implied volatilities and realized volatilities. Using near-the-money options for 10 firms over the sample period from April 2005 to April 2010, we first demonstrate that the implied volatilities for most firms don’t have additional information beyond what are already contained in historical volatilities. However, the implied volatilities with some specific remaining maturities for two firms dominate historical volatilities in explaining the future realized volatilities. Second, we find that during the period before global financial crisis, the implied volatilities are systematically lower than the future realized volatilities whereas this reversal disappears after the year 2008. This finding suggests that there’s a possibility of the risk loving behavior of the investors in OTC individual stock options market during the pre-global crisis period. Finally, through the comparative analysis of the KOSPI200 index options quoted OTC over the same sample period, we conclude that the OTC individual stock options market has distinctive characteristics like the KRW/USD OTC currency options market.

The purpose of this research is to determine whether the trading of equity index futures contracts on the South African Futures Exchange (SAFEX) results in an increase in the volatility of the underlying spot indices. Since equity index futures contracts were first listed in the USA in 1975, various studies have been undertaken to determine whether the volatility of shares in the underlying indices increases as a result of the trading of such futures contracts. These studies have lead to the development of two schools of thought: [a] Trading activity in equity index futures contracts leads to an increase in the volatility of index shares. [b] Trading activity in equity index futures contracts does not lead to an increase in the volatility of the index shares and could in fact lead to greater stability in equity markets. Although some evidence of higher volatility in expiration periods was found, volatility in the expiration periods was not consistently higher than in the corresponding pre‐expiration period.

The purpose of this paper is to amend the New Keynesian Phillips Curve (NKPC) model to include inflation volatility. It provides results on the determinants of inflation volatility and expected inflation volatility for ordinary least squares and autoregressive distributed lags (1,1) models and for change in inflation volatility and change in expected inflation volatility using error correction mechanism (ECM) models. Output gap affects change in expected inflation volatility alone (in the ECM model) and not in the other models. Major determinants of inflation volatility and expected inflation volatility are identified. To the best of the authors knowledge this is the first paper to augment the NKPC to include inflation volatility.

Recent analysis has indicated the importance of inflation volatility for the monetary transmission mechanism in India (Kapur and Behera, 2012). In the analysis of such monetary policy mechanisms the NKPC has proved to be a useful tool. Thus Patra and Ray (2010) for India and Brissimis and Magginas (2008) for the USA find considerable support for the standard NKPC. The purpose of this paper is to synthesize and integrate these two models by extending the standard NKPC framework to include inflation volatility and test its significance for the case of India.

In the case of inflation volatility output gap, lagged output gap and lagged inflation volatility are all insignificant. The level of inflation has a negative significant impact whereas the level of expected inflation has a positive and significant impact. In the case of expected inflation volatility lagged output gap has a negative and significant impact, the price level has a positive and significant impact whereas expected price has a negative and weakly significant impact. ECM reveals change in inflation variability falls significantly with lagged inflation volatility and lagged inflation and less significantly with change in expected inflation. It rises with lagged expected inflation although the coefficient is only weakly significant. Lagged output gap and change in output gap are insignificant.

This paper makes two original contributions. First, it extends the New Keynesian framework to include inflation volatility. Second, it estimates this model for India. To the best of the authors knowledge this is the first paper to make these contributions.

The development of standardized measures of institution‐wide volatility exposures has so far lagged that for measures of asset price and interest‐rate exposure—largely because it is difficult to reconcile the various mathematical models used to value options. Recent mathematical results, however, can be used to construct standardized measures of volatility exposure. We consider here techniques for reconciling “vegas” for financial options valued using stochastic models that may be mathematically inconsistent with each other.

The purpose of this paper is to examine whether stock market liberalization creates excess stock return volatility in the Qatar Exchange (QSC).

The study utilizes two methods, simple analysis of variance and the EGARCH model with dummy variables.

Results reveal no change in market volatility following the partial removal of the restrictions on foreign participation. Results suggest, however, that the degree of persistence in volatility is high, which implies that once volatility increases it remains high over a long run. In addition, conditional volatility tends to rise when the absolute value of the standardized residuals was large. While, contrary to what has been found in the literature, the return volatility seems to be symmetric.

The finding of volatility persistence and clustering might imply an inefficient stock market. Therefore, policy makers should emphasize and direct their attention toward increasing the efficiency of the stock market.

Being able to make predictions about financial market volatility is of special importance to investors and policy makers since it makes available to them a measure of risk exposure in their investments and decisions.

This paper provides a contribution to the empirical literature on stock market volatility. It is the only study, to the authors' knowledge, that investigates the issue of QSC liberalization and volatility. The authors believe that QSC has its own unique characteristics, and the results of the study depend mainly on the market's specific conditions, the quality of its financial institutions and the extent of financial liberalization obtained.

The Chinese stock market is a typical emerging market with special features that are very different from those of mature markets. The objective of this study is to investigate whether and how these features affect the volatility‐volume relation for Chinese stocks.

This paper examines the roles of the number of trades, size of trades, and share volume in explaining the volatility‐volume relation in the Shanghai Stock Exchange with high frequency trade data used.

The results confirm that the volatility‐volume relation is driven mainly by the number of trades on the Chinese stock market. The number of trades explains the volatility‐volume relation better than the size of trades. Furthermore, some results are obtained that differ from those of mature markets, such as the US market. The results show that the second largest sized trades affect the volatility more than other trades on the Chinese market.

The results show that, in the Shanghai Stock Exchange, informed traders camouflage their private information or manipulation behavior through the second largest sized trades. The results may have important implications for work explaining the volatility‐volume relation on the Chinese stock market, further providing a reference by which to regulate emerging markets.

The purpose of this paper is to investigate the potential link between remittances and economic volatility in small island developing states.

The paper estimates a panel data model using a database containing 20 small island developing states (SIDS) observed over annual intervals between 1986 and 2005.

The results suggest that, in general, remittance flows have a stabilising influence on output and investment volatility. However, given the importance of these flows to SIDS, the volatility of remittances also has a significant and positive impact on both investment and consumption volatility.

The policy implications of the study's findings is that SIDS (similar to how oil‐producing nations take oil price fluctuations into account when considering policy changes) may have to monitor and forecast future remittance flows and take these projections into account when making changes to either their monetary or fiscal policy stance.

Workers' remittances have grown dramatically worldwide, particularly in SIDS, where they constitute one of the main sources of foreign exchange. Given the importance of these flows to economic growth and development in these countries, this study examines the potential link between remittances and economic volatility.